Markovian Multiple Change-Point Modeling for Software Reliability Assessment

2020 ◽  
Vol 27 (06) ◽  
pp. 2050017
Author(s):  
Shinji Inoue ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Reliability Assessment ◽  
Testing Time ◽  
Modeling Framework ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Testing Environment ◽  
Software Failure ◽  
Testing Phase

We discuss software reliability modeling reflecting actual situation in a testing phase based on a Markovian software reliability modeling framework. Concretely, we discuss Markovian imperfect debugging modeling for software reliability assessment with multiple changes of testing environment. Testing-time changing the testing environment is called change-point. Taking into account the effect of change-point in software reliability growth modeling is expected to improve the accuracy of software reliability assessment because it is often observed that the stochastic characteristic of software failure-occurrence or fault-detection phenomenon is changed in an actual testing phase. Numerical examples for software reliability assessment based on our proposed approach are also shown by using actual software failure-occurrence time data. Further, we discuss the usefulness of considering the effect of the imperfect debugging and the multiple change-point into software reliability modeling by comparing the estimated behavior of the mean time between software failures based on our model and the existing related models.

Markovian Software Reliability Modeling with Change-Point

2018 ◽  
Vol 25 (02) ◽  
pp. 1850009 ◽  
Author(s):  
Shinji Inoue ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Reliability Assessment ◽  
Testing Time ◽  
Reliability Growth ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Modeling Approach ◽  
Semi Markov Process ◽  
Software Reliability Growth

We discuss a Markovian modeling approach for software reliability assessment with the effects of change-point and imperfect debugging environment. Testing-time when the characteristic of the software failure-occurrence or fault-detection phenomenon changes notably is called change-point. Taking into account the effect at change-point in software reliability growth modeling is important to improve the accuracy of software reliability assessment. Our modeling approach describes a software reliability growth process with not only the effect of change-point but also the imperfect debugging activities based on a semi-Markov process for reflecting actual situation of debugging activities. Finally, we show numerical examples of our model for software reliability analysis and check the performance of our model with an existing Markovian software reliability growth model by using actual data.

SOFTWARE RELIABILITY ASSESSMENT USING EXPONENTIAL-TYPE CHANGE-POINT HAZARD RATE MODELS

2014 ◽  
Vol 21 (04) ◽  
pp. 1450019 ◽  
Author(s):  
SHIHO HAYASHIDA ◽  
SHINJI INOUE ◽  
SHIGERU YAMADA
Keyword(s):  
Exponential Type ◽  
Software Reliability ◽  
Change Point ◽  
Hazard Rate ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Testing Environment ◽  
Software Failure ◽  
Type Change ◽  
Hazard Rate Models

We discuss software hazard rate modeling with a change of testing-environment and a software reliability assessment method based on the proposed software hazard rate models. A software hazard rate model is known as one of the important and useful mathematical models for describing the software failure-occurrence phenomenon and conducting quantitative software reliability assessment. Taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment because it is said that such approach enables us to conduct more plausible software reliability assessment reflecting the actual testing-environment. Especially in this paper, we develop exponential-type software hazard rate models with effect of change-point and a software reliability assessment method based on our models. Finally, we show numerical examples for our models and results of model comparisons with existing software hazard rate models by using actual data.

EXTENDED HAZARD RATE MODELS FOR SOFTWARE RELIABILITY ASSESSMENT WITH EFFECT AT CHANGE-POINT

2013 ◽  
Vol 20 (02) ◽  
pp. 1350009 ◽  
Author(s):  
SHINJI INOUE ◽  
SHIHO HAYASHIDA ◽  
SHIGERU YAMADA
Keyword(s):  
Software Reliability ◽  
Hazard Rate ◽  
Reliability Assessment ◽  
Reliability Growth ◽  
Testing Environment ◽  
Software Failure ◽  
Testing Phase ◽  
Hazard Rate Model ◽  
Hazard Rate Models ◽  
Software Reliability Growth

A software hazard rate model is known as one of the important and useful mathematical models for describing the software failure occurrence phenomenon observed in a testing phase. It is difficult to say that the testing environment always constant during a testing phase due to changing the specification and fault target and so forth. Therefore, taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment. In this paper, we develop extended software hazard rate models based on well-known Jelinski–Moranda and Moranda models, by considering with a change of testing environment. Especially in this paper, we incorporate the uncertainty of the effect of the change on the software reliability growth process into the software hazard rate modeling. Finally, we show numerical examples for our models and results of model comparisons by using actual data.

An All-Stage Truncated Multiple Change Point Model for Software Reliability Assessment

2015 ◽  
Vol 22 (04) ◽  
pp. 1550017 ◽  
Author(s):  
Shinji Inoue ◽  
Saki Taniguchi ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Reliability Assessment ◽  
Point Model ◽  
Modeling Framework ◽  
Reliability Modeling ◽  
Software Failures ◽  
Modeling Approach ◽  
Counting Data ◽  
Change Point Model

We propose a software reliability growth modeling framework with multiple change point occurrence environment. Especially in our modeling framework, the probability distribution of the initial fault content follows a zero-truncated Poisson distribution. Therefore, our modeling approach in this paper can derive the proper mean time between software failures (MTBF), which is one of the important reliability assessment measures and is not able to derive in the usual nonhomogeneous Poisson process modeling, which is one of the well-known software reliability modeling approach. This paper also show numerical examples of application of our proposed multiple change point model to software reliability assessment by using actual fault counting data.

TWO-DIMENSIONAL CHANGE-POINT MODELING FOR SOFTWARE RELIABILITY ASSESSMENT

2010 ◽  
Vol 17 (06) ◽  
pp. 531-542 ◽  
Author(s):  
SHINJI INOUE ◽  
KEISUKE FUKUMA ◽  
SHIGERU YAMADA
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Growth Process ◽  
Reliability Assessment ◽  
Testing Time ◽  
Reliability Growth ◽  
Two Dimensional ◽  
Occurrence Time ◽  
Software Failure ◽  
Software Reliability Growth

Most of software reliability growth models (SRGMs) describe a software reliability growth process depending on only testing-time. However, it is said that a software reliability growth process in an actual testing-phase of a software development process depends on not only testing-time but also testing-effort factors. And we often observe a phenomenon that stochastic characteristics of the software failure-occurrence time or the software failure-occurrence time-interval changes notably in an actual testing-phase. The testing-time when such phenomenon is observed is called change-point. It is said that the effect of change-point on the software reliability growth process influences accuracy for software reliability assessment based on conventional SRGMs. This paper discusses a two-dimensional software reliability growth modeling with change-point for describing an actual phenomenon being related to the software reliability growth process. Further, we show examples of the applications of software reliability assessment based on our two-dimensional SRGM by using actual data.

GENERALIZED MARKOVIAN SOFTWARE RELIABILITY MODELING AND ITS ALTERNATIVE CALCULATION

2009 ◽  
Vol 16 (05) ◽  
pp. 385-402 ◽  
Author(s):  
KOICHI TOKUNO ◽  
TAKAHIRO KODERA ◽  
SHIGERU YAMADA
Keyword(s):  
Approximation Method ◽  
Software Reliability ◽  
Reliability Assessment ◽  
Time Interval ◽  
Cumulative Number ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Software Failures ◽  
Software Reliability Model ◽  
Assessment Measures

In this paper, we attempt generalization of the Markovian software reliability model (MSRM). Defining the stochastic process whose state space is the cumulative number of corrected faults, we show the theoretical framework of the MSRM by assuming that the time interval between software failures is distributed generally. We also consider the imperfect debugging environment where the debugging activities are uncertain. Several software reliability assessment measures are expressed with the distribution of the transition time between arbitrary two states. Furthermore, we propose the approximation method for practical computation of the quantitative measures. Finally, we investigate the validity of our proposed approximation method.

scholarly journals Software Reliability Modeling Incorporating Fault Detection and Fault Correction Processes with Testing Coverage and Fault Amount Dependency

Mathematics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 60
Author(s):  
Qiuying Li ◽  
Hoang Pham
Keyword(s):  
Fault Detection ◽  
Software Reliability ◽  
Estimation Methods ◽  
Time Dependency ◽  
Modeling Framework ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Detection Process ◽  
Correction Process ◽  
Testing Coverage

This paper presents a general testing coverage software reliability modeling framework that covers imperfect debugging and considers not only fault detection processes (FDP) but also fault correction processes (FCP). Numerous software reliability growth models have evaluated the reliability of software over the last few decades, but most of them attached importance to modeling the fault detection process rather than modeling the fault correction process. Previous studies analyzed the time dependency between the fault detection and correction processes and modeled the fault correction process as a delayed detection process with a random or deterministic time delay. We study the quantitative dependency between dual processes from the viewpoint of fault amount dependency instead of time dependency, then propose a generalized modeling framework along with imperfect debugging and testing coverage. New models are derived by adopting different testing coverage functions. We compared the performance of these proposed models with existing models under the context of two kinds of failure data, one of which only includes observations of faults detected, and the other includes not only fault detection but also fault correction data. Different parameter estimation methods and performance comparison criteria are presented according to the characteristics of different kinds of datasets. No matter what kind of data, the comparison results reveal that the proposed models generally give improved descriptive and predictive performance than existing models.

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